Intelligent power converter system based on adaptive load regulation and control method thereof

Abstract

The application relates to the technical field of power conversion, and discloses an intelligent power converter system based on adaptive load adjustment and a control method thereof. The system comprises a power converter body, a plurality of different types of sockets arranged on the power converter body, and a load sensing sensor, a micro control unit, a voltage reduction circuit and a bridge circuit arranged in the power converter body. The load sensing sensor is electrically connected with the micro control unit, is used for monitoring the power demand of the equipment connected with each socket in real time, and transmits corresponding monitoring signals to the micro control unit. The micro control unit is electrically connected with the voltage reduction circuit and the bridge circuit, is used for controlling the voltage reduction circuit and the bridge circuit to adjust the output voltage and current according to the monitoring signals transmitted by the load sensing sensor, and controls the voltage reduction circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the equipment power demand monitored by the load sensing sensor, so that adaptive load adjustment of each socket is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power conversion, and in particular to an intelligent power converter system based on adaptive load regulation and a control method thereof. BACKGROUND

[0002] In traditional power conversion devices, the power converter usually adopts a fixed voltage output mode. For example, common power strips, chargers, etc. can only provide a single or preset voltage / current specification, and cannot dynamically adjust the output parameters according to the actual power demand of the connected device. The specific deficiencies are as follows:

[0003] 1. Lack of intelligent load recognition capability: existing devices cannot monitor the power demand of the connected device in real time. For different types of electrical equipment (such as mobile phones, laptops, small household appliances, etc.), a fixed voltage output is used, which causes the problem of "overvoltage power supply" when small power devices are connected, resulting in waste of electrical energy and increasing the risk of device aging.

[0004] 2. Insufficient voltage conversion flexibility: when the input mains voltage does not match the required voltage of the device (for example, 110V devices connected to 220V mains or vice versa), traditional converters rely on external transformers or fixed step-down modules, and cannot achieve dynamic voltage conversion through built-in circuits, and do not support independent adjustment of multiple outlets, limiting the application scenarios.

[0005] 3. Single energy efficiency optimization method: existing solutions only improve energy efficiency through fixed-efficiency circuit design, lack dynamic adjustment strategies based on real-time load data, and especially in low-load working conditions, the circuit itself has a high loss ratio, resulting in low overall energy conversion efficiency, which does not meet the green energy development needs.

[0006] 4. Safety protection mechanism lags behind: the overvoltage / overcurrent protection of traditional devices relies on hardware threshold triggering, and cannot predict based on device type and real-time power demand, which may cause device damage due to voltage fluctuations or parameter mismatches, and the safety is insufficient.

[0007] Therefore, an intelligent power converter system based on adaptive load regulation is needed to solve at least one of the above problems. SUMMARY

[0008] The present application provides an intelligent power converter system based on adaptive load regulation and a control method thereof, which aims to solve the problem that in traditional power conversion devices, the power converter usually adopts a fixed voltage output mode, for example, common power strips, chargers, etc. can only provide a single or preset voltage / current specification, and cannot dynamically adjust the output parameters according to the actual power demand of the connected device.

[0009] In a first aspect, the present application provides an intelligent power converter system based on adaptive load regulation, comprising:

[0010] A power converter body is provided with a plurality of different types of sockets, and is internally provided with a load sensing sensor, a micro control unit, a step-down circuit and a bridge circuit; the load sensing sensor is electrically connected to the micro control unit, for real-time monitoring of the power demand of the device connected to each socket and transmitting the corresponding monitoring signal to the micro control unit; the micro control unit is electrically connected to the step-down circuit and the bridge circuit, respectively, for controlling the step-down circuit and the bridge circuit to adjust the output voltage and current according to the monitoring signal transmitted by the load sensing sensor;

[0011] When the device connected to the socket needs low-voltage direct-current power supply, the micro control unit controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current; when the socket is connected to different input mains voltage, the micro control unit controls the bridge circuit to convert the input mains voltage to the target voltage suitable for the socket; the micro control unit controls the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor, so as to realize adaptive load adjustment for each socket.

[0012] In some embodiments, when the device connected to the socket needs low-voltage direct-current power supply, the micro control unit controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current, including: when the device is inserted into the socket, the load sensing sensor obtains the rated voltage parameter of the device in real time, and the micro control unit controls the step-down circuit to step down from the input alternating voltage to the direct-current voltage required by the device according to the rated voltage parameter, and dynamically adjusts the current according to the real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

[0013] In some embodiments, when the socket is connected to different input mains voltage, the micro control unit controls the bridge circuit to convert the input mains voltage to the target voltage suitable for the socket, including: when the socket is connected to the mains as input, the bridge circuit converts the mains power corresponding to the mains to the target voltage suitable for the socket according to the socket specification parameter, and monitors the frequency and phase of the output voltage in real time through the micro control unit during the conversion process, ensures that the distortion degree of the converted voltage waveform is less than the preset distortion degree, and realizes the voltage level matching and bidirectional transmission of electric energy between different sockets through the switching tube on-off frequency adjustment of the bridge circuit.

[0014] In some embodiments, the micro control unit is configured to automatically adjust the output voltage and current of the corresponding outlet based on the power requirement of the device detected by the load sensing sensor, so as to achieve adaptive load adjustment for each outlet, including: when the load sensing sensor detects that the power of the device connected to the outlet is less than a preset threshold, the micro control unit adjusts the output voltage to the minimum effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the minimum effective voltage, so that the device reduces the energy loss caused by the internal resistance of the circuit while meeting the normal operation.

[0015] In some embodiments, the micro control unit is further configured to automatically identify the type of the device based on the device start current waveform and continuous power data collected by the load sensing sensor, and match the optimal voltage adjustment strategy according to a preset device type database, wherein the preset device type database includes voltage-power matching parameters of a plurality of power consuming devices.

[0016] For example, the micro control unit stores the power adjustment data of the historical connected devices, dynamically optimizes the response speed and accuracy of the voltage adjustment by analyzing the voltage adaptation process when the device is repeatedly accessed, so that the voltage adjustment time is shortened when the same type of device is accessed again.

[0017] In some embodiments, the load sensing sensor includes a current transformer and a voltage sensor, which are integrated on the power supply circuit of each outlet to respectively collect the input current and port voltage of the device in real time, and the micro control unit calculates the real-time power based on the collected data and performs abnormality detection, and when it is detected that the power mutation exceeds a preset mutation range of the rated value, triggers the overvoltage protection or overcurrent protection mechanism to cut off the power supply of the corresponding outlet.

[0018] In some embodiments, the power converter body is internally provided with a separate power management module, the power management module includes a filter circuit and an energy storage capacitor, the filter circuit is used to filter out the high-frequency noise generated during the operation of the voltage reduction circuit and the bridge circuit, and the energy storage capacitor maintains stable power supply when the input voltage fluctuates instantaneously, so as to ensure the continuous monitoring function of the micro control unit and the load sensing sensor.

[0019] In some embodiments, the power converter body is provided with a human-computer interaction interface on the surface, the human-computer interaction interface includes a state indicating lamp and a parameter adjustment button, and the voltage upper limit and current protection threshold of any outlet are set through the adjustment button.

[0020] In a second aspect, the application provides a control method of an intelligent power converter system based on adaptive load adjustment, which is applied to the intelligent power converter system based on adaptive load adjustment provided in any of the embodiments of the application; the method comprises:

[0021] When the socket-connected device requires low-voltage DC power supply, the control buck circuit reduces the input voltage to the required voltage of the device and adjusts the output current;

[0022] When the socket connects different mains voltage inputs, the control bridge circuit converts the input mains voltage to the target voltage suitable for the socket;

[0023] According to the device power demand monitored by the load sensing sensor, the control buck circuit and the bridge circuit automatically adjust the output voltage and current of the corresponding socket to achieve adaptive load regulation for each socket.

[0024] The present application provides a fascia gun adaptive frequency adjustment and muscle relaxation intensity control method and system, aiming to solve the problem that the prior art has not disclosed a power converter system integrating a load sensing sensor, a micro control unit (MCU), a buck circuit and a bridge circuit, and realizing independent adaptive adjustment of multiple sockets through intelligent algorithm. The core defect of the existing scheme is "passive fixed output", not "active sensing-dynamic adaptation". The present application can automatically identify the voltage and current requirements of different devices such as mobile phones and small household appliances by real-time monitoring of the device power demand of each socket through the load sensing sensor, combined with the dynamic control strategy of the micro control unit, realizing intelligent conversion from 110V / 220V mains to 5V, 9V low-voltage DC or between different mains voltages, supporting a wide range of device types and application scenarios. For low-power devices, the output voltage and current are automatically reduced to avoid excessive energy consumption caused by traditional fixed high-voltage power supply, the power conversion efficiency can be improved, the energy waste is significantly reduced, and the energy saving and emission reduction demand is met. Through the cooperative control of the buck circuit (BUCK circuit) and the bridge circuit (H-Bridge circuit), the damage to the device caused by voltage abnormalities is effectively avoided, and the power supply reliability is improved. By integrating load monitoring, parameter adjustment and protection mechanism into the same control system, the system responds in real time to changes in device power, quickly triggers overvoltage / overcurrent protection when a power surge is detected, and compared with the traditional lag protection mechanism, the response time is shortened to within 200 milliseconds, and the system safety is improved. Through the built-in power classification algorithm and adaptive learning module (dependent claim expansion content), the system can automatically match the optimal voltage strategy and optimize the adjustment accuracy without user manual setting, realizing the intelligent power supply experience of "plug and play", which is significantly different from the traditional manual intervention or fixed parameter power conversion equipment.

[0025] In summary, the present application solves the problems of poor adaptability, low energy efficiency and insufficient safety in the prior art through the core architecture of "load sensing-intelligent decision-dynamic adjustment", providing a new technical path for the intelligent and efficient development of power conversion equipment, and having significant creativity and practical value.

[0026] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present application. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0028] Figure 1 is a structural schematic block diagram of an intelligent power converter system based on adaptive load regulation provided by an embodiment of the present application;

[0029] Figure 2 is a structural schematic diagram of a power converter body provided by an embodiment of the present application;

[0030] Figure 3 is a step schematic flow chart of a control method of an intelligent power converter system based on adaptive load regulation provided by an embodiment of the present application;

[0031] Figure 4 is a structural schematic block diagram of a micro control unit provided by an embodiment of the present application.

[0032] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present application. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0034] The flow charts shown in the drawings are only exemplary and are not necessarily required to include all the contents and operations / steps, and are not necessarily executed in the described order. For example, some operations / steps can be decomposed, combined or partially merged, so that the actual execution order can be changed according to the actual situation.

[0035] It should be understood that, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", etc. are used to distinguish the same items or similar items with basically the same function and role. Those skilled in the art can understand that the terms "first", "second", etc. do not limit the quantity and execution order, and the terms "first", "second", etc. also do not necessarily mean different.

[0036] It should be understood that the terms used in the present application specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless otherwise clear from the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0037] It should also be understood that the term "and / or" used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0038] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features in the embodiments can be combined with each other without conflict.

[0039] In a conventional power conversion device, the power converter usually adopts a fixed voltage output mode, for example, a common power strip, charger, etc. can only provide a single or preset voltage / current specification, and cannot dynamically adjust the output parameters according to the actual power demand of the connected device. The specific deficiencies are as follows:

[0040] 1. Lack of load intelligent recognition capability: existing devices cannot monitor the power demand of the connected device in real time, and for different types of electrical equipment (such as mobile phones, notebook computers, small household appliances, etc.), a fixed voltage output is used, which causes the problem of "overvoltage power supply" when a small power device is connected, resulting in waste of electrical energy and increasing the risk of device aging.

[0041] 2. Insufficient voltage conversion flexibility: when the input mains voltage and the required voltage of the device do not match (for example, 110V device connected to 220V mains or vice versa), the conventional converter relies on an external transformer or a fixed step-down module, and cannot achieve dynamic voltage conversion through an internal circuit, and does not support independent adjustment of multiple outlets, and the application scenarios are limited.

[0042] 3. Single energy efficiency optimization means: existing solutions only improve energy efficiency through fixed efficiency circuit design, lack dynamic adjustment strategies based on real-time load data, and especially in low load working conditions, the circuit itself loss ratio increases, the overall energy conversion efficiency is low, and it does not meet the green energy development needs.

[0043] 4. Security protection mechanism lag: The overvoltage / overcurrent protection of traditional devices relies on hardware threshold triggering and cannot make predictions in combination with device types and real-time power requirements, which may cause device damage due to voltage fluctuations or parameter mismatches, and the security is insufficient.

[0044] Therefore, there is an urgent need for an intelligent power converter system based on adaptive load regulation to solve at least one of the above problems.

[0045] To solve the above problems, please refer to Figures 1 to 2 The application provides an intelligent power converter system based on adaptive load regulation, comprising: a power converter body, a plurality of different types of sockets are arranged on the power converter body, and a load sensing sensor, a micro control unit, a step-down circuit and a bridge circuit are built-in in the power converter body; the load sensing sensor is electrically connected with the micro control unit, for monitoring the power demand of the device connected to each socket in real time and transmitting the corresponding monitoring signal to the micro control unit; the micro control unit is electrically connected with the step-down circuit and the bridge circuit respectively, for controlling the step-down circuit and the bridge circuit to adjust the output voltage and current according to the monitoring signal transmitted by the load sensing sensor; when the device connected to the socket needs low-voltage direct-current power supply, the micro control unit controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjusts the output current; when the socket is connected with different input voltages of commercial power, the micro control unit controls the bridge circuit to convert the input commercial power voltage into the target voltage suitable for the socket; the micro control unit controls the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the device power demand monitored by the load sensing sensor, so as to realize adaptive load regulation for each socket.

[0046] Specifically, the intelligent power converter system takes the power converter body as the carrier, realizes adaptive regulation of the load by integrating the following core functional modules: multi-type socket design: the body is provided with a plurality of different types of sockets (such as USB-A, USB-C, AC jack, etc.), which supports different devices such as mobile phones, laptops, small household appliances, etc. to access, and is compatible with a variety of interface forms and power demands. Figure 2As shown, the body can also be integrated with power input box, heat dissipation hole, power button and display light and other modules. Load sensing sensor: each socket is built-in independent voltage / current sensor (or integrated power sensor), real-time monitoring of the real-time power (P=UxI) of the connected device, voltage, current and other parameters, and transmitting monitoring signals (analog or digital) to the micro control unit (MCU). Micro control unit (MCU): system core control module, built-in load identification algorithm and regulation strategy. Its functions include: receiving load sensing sensor data, analyzing device power demand (such as identifying mobile phone fast charging protocol, household appliance rated voltage, etc.); according to the preset rules (such as device type database, safety threshold), generate control instructions, drive the buck circuit and bridge circuit to dynamically adjust the output parameters; support multi-socket independent control, ensure that the outputs of each socket do not interfere with each other. Buck circuit: using DC-DC conversion module (such as Buck circuit), when the device needs low voltage direct current power supply (such as 5V / 9V / 12V mobile phone charging), MCU controls the buck circuit to reduce the high voltage direct current voltage after rectification of the input mains (such as 220V AC) to the voltage required by the device, and adjusts the output current through PWM (pulse width modulation) technology to meet the power demand. Bridge circuit: composed of full-bridge rectifier and inverter unit, used to handle different mains voltage input scenarios (such as 110V and 220V conversion). When the input mains voltage and the rated voltage of the device do not match, the bridge circuit converts the input voltage to the target voltage (such as 220V input to 110V output, or vice versa) through rectification, inversion or buck / boost conversion, supporting bidirectional voltage conversion.

[0047] The system realizes adaptive load regulation through a "perception-treatment-regulation" closed loop: load perception: sensors collect voltage and current signals of each socket in real time, calculate instantaneous power, identify device types (such as distinguishing between mobile phones and laptops through characteristic current waveforms) or directly read device communication protocols (such as voltage requests in the PD fast charging protocol). Strategy processing: the MCU compares real-time monitoring data with the preset device power database (which stores parameters such as the rated voltage, current, and safety threshold of common devices) to determine whether output adjustment is needed. For example, if a low-power device (such as a mobile phone) is connected and the actual demand power is lower than the fixed output power, the buck circuit is triggered to reduce the voltage to the device's rated value, avoiding "overvoltage power supply"; if a 110V device is connected to 220V mains, the bridge circuit starts the inverter function to convert 220V AC to 110V AC, without the need for an external transformer. Dynamic regulation: for each socket, the MCU independently controls the working parameters of the buck circuit or bridge circuit: DC output scenario: by adjusting the PWM duty cycle of the buck circuit, the output voltage (such as 5V, 9V, 12V) and current (such as 1A, 2.4A, 3A) are accurately controlled to match the device's real-time demand; AC voltage conversion scenario: the bridge circuit converts input AC to DC through full-bridge rectification, and then generates the target AC voltage (such as 50Hz / 60Hz, 110V / 220V) through the inverter module, supporting wide voltage input and multiple standard output.

[0048] The load perception module can use high-precision Hall sensors or shunt resistors to collect current and divide resistors to collect voltage. The signals are converted to digital quantities by ADC (analog-to-digital converter) and input to the MCU. For devices that support protocol communication (such as USB PD devices), the device's requested voltage / current parameters are read through an interface chip (such as a PD controller) to improve identification accuracy.

[0049] The buck circuit implementation can use a synchronous Buck converter (such as LM2596, TPS5430) that supports a wide input voltage range (such as 40V-300V DC) and adjustable output voltage (1.23V-37V) with an efficiency of over 90%. The MCU configures the feedback resistor or PWM frequency of the buck chip through SPI / I2C interface to dynamically adjust the output voltage, while controlling the output current not to exceed the device's rated value through a current loop.

[0050] The bridge circuit implementation can use a bridge rectifier (such as GBJ2006) in the rectification part to convert input AC to pulsating DC, which is then smoothed by a filter capacitor and enters the inverter module. The inverter part uses an IGBT or MOSFET full-bridge circuit, and the MCU generates an SPWM (sine wave pulse width modulation) signal to drive the switch tube, converting DC to the target AC voltage (such as 110V / 60Hz) and filtering out harmonics through an LC filter.

[0051] Multi-outlet independent control is achieved by corresponding independent sensors, voltage reduction / bridge circuit submodules for each outlet, and MCU control through time division multiplexing or parallel IO ports, ensuring the adjustment accuracy when multiple devices are connected simultaneously.

[0052] The device type identification algorithm stores the power range and voltage / current waveform characteristics of common devices (such as the sudden increase in current during the initial fast charging stage of a mobile phone and the stable high power demand of a laptop) by establishing a device feature database. It uses pattern matching algorithms (such as threshold comparison and machine learning classification) to identify the device type based on real-time power curves and dynamically calls corresponding adjustment strategies (such as prioritizing stable voltage for a laptop and energy efficiency optimization for a mobile phone).

[0053] The dynamic adjustment logic includes: low voltage direct current scenario: if the actual demand voltage of the device is lower than the current output voltage, the MCU gradually reduces the output voltage of the voltage reduction circuit to the rated value of the device while limiting the current to not exceed the maximum allowed value of the device; mains conversion scenario: when the difference between the input voltage and the rated voltage of the device exceeds the preset threshold (such as ±10%), the bridge circuit is triggered to start conversion, and the output voltage fluctuation is monitored in real time during the conversion process, and the output is stabilized through a PID (proportional-integral-derivative) algorithm.

[0054] The safety protection mechanism includes: preset overvoltage (such as output voltage exceeding rated value by 15%), overcurrent (exceeding device rated current by 20%), and overheat (temperature exceeding 85°C) thresholds. Once triggered, the MCU immediately cuts off power to the corresponding outlet and alerts through LED or APP. The protection threshold is dynamically adjusted according to the device type (such as allowing slightly higher current fluctuation for small household appliances and setting stricter thresholds for precision electronic devices), achieving "predictive protection" rather than simple hardware triggering.

[0055] User interface: optional LED screen displays real-time voltage, current, and power of each outlet, or connects to the APP through Bluetooth / Wi-Fi, supporting manual setting of output parameters (requires permission control to avoid safety risks); firmware upgrade: supports OTA (over-the-air) update of device feature database and adjustment algorithm to adapt to the access needs of new devices (such as higher power fast charging devices).

[0056] By real-time power monitoring and device type recognition, it provides matching voltage / current for small power devices (such as mobile phones), eliminates the waste of electrical energy caused by "fixed high voltage output", and prolongs the service life of the device. The built-in bridge circuit supports 110V and 220V mains bidirectional conversion, without the need for external transformers, compatible with global voltage standards; multiple outlets independently adjusted allow simultaneous access to devices with different voltage requirements (such as powering a 220V coffee maker and a 110V shaver at the same time), suitable for travel, multi-device office and other scenarios. Based on real-time load adjustment strategy (such as reducing circuit loss at low load and optimizing conversion efficiency at full load), compared with traditional fixed efficiency design, the overall energy efficiency of the system is improved, especially at light load, the self-loss is significantly reduced. Combined with device type and real-time data prediction protection (such as adjusting output in advance before detecting abnormal voltage fluctuation), it avoids the lag of traditional hardware threshold triggering, reduces the risk of device damage caused by overvoltage / overcurrent, and improves safety.

[0057] Supports USB, AC and other types of sockets, adapts to a wide range of devices from 5V mobile phones to 220V household appliances, replaces multiple single-function converters, simplifies user device management; each socket works independently, and single-socket failure does not affect the operation of other sockets, improving system reliability; hardware is extensible (such as adding wireless charging modules), suitable for future device upgrades.

[0058] This system combines "hardware intelligence + software strategy" to upgrade traditional power converters from "fixed parameter output" to "dynamic adaptive adjustment", not only solving the problems of energy waste and scene limitation, but also meeting the current development trend of "energy saving and emission reduction" and "device intelligence", with wide application prospects in household, office and industrial applications.

[0059] In some embodiments, when a device connected to the socket needs low-voltage direct current power, the microcontroller unit controls the voltage reduction circuit to reduce the input voltage to the voltage required by the device and adjust the output current, including: when the device is inserted into the socket, the load sensing sensor obtains the rated voltage parameter of the device in real time, and the microcontroller unit controls the voltage reduction circuit to step down from the input alternating current voltage to the direct current voltage required by the device, and dynamically adjusts the current according to the real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

[0060] When a device connected to the socket needs low-voltage direct current power, the system obtains the rated voltage parameter of the device through the load sensing sensor, and the microcontroller unit (MCU) controls the voltage reduction circuit to step down from the input alternating current voltage (such as 220V AC) to the direct current voltage required by the device (such as 5V / 9V / 12V), and dynamically adjusts the current according to the real-time power, to ensure that the output voltage fluctuation range is within the preset fluctuation range (such as ±5%) of the rated voltage.

[0061] Voltage acquisition: For devices supporting communication protocols (such as USB PD devices), read the voltage request (such as "need 9V / 2A") sent by the device through the interface chip (such as RT5400); for non-smart devices (such as ordinary USB devices), collect the current / voltage data at the initial access through the load sensing sensor, and infer the rated voltage combined with the built-in default parameters (such as 5V standard).

[0062] Step-down control: through the step-down circuit, use multi-stage Buck converter cascade or single-stage adjustable Buck circuit (such as LM2596), MCU controls the switch tube through PWM signal, and reduces the voltage in stages (for example, from 310V DC after rectification of 220V AC, first reduce to 20V DC, and then reduce to target voltage 9V DC), each step-down step is not more than 20% of the target voltage, to avoid voltage sudden drop impact on the device.

[0063] Dynamic current regulation: by real-time calculation of device power (P=U×I), MCU adjusts the output current of Buck circuit through current feedback loop, for example, when the device enters the charging trickle current stage (power reduction), automatically reduce the current to 0.5A, while real-time monitoring the output voltage through ADC, to ensure that the fluctuation is not more than ±5%.

[0064] Avoid the "overvoltage" problem of traditional fixed voltage output, for example, provide accurate 5V±0.25V voltage for 5V mobile phone, reduce the loss of internal voltage stabilizer of the device, and prolong the battery life; step-down prevents inrush current, especially suitable for capacitive load devices (such as wireless earphone charging box), reduces the risk of voltage impact during startup; support DC output devices from 3.3V to 20V, without replacing the converter, improve the universality of the socket.

[0065] In some embodiments, when the socket is connected to different mains voltage inputs, the microcontroller controls the bridge circuit to convert the input mains voltage to a target voltage suitable for the socket, including: when the socket is connected to the mains as input, the bridge circuit converts the mains power corresponding to the mains voltage to a target voltage suitable for the socket according to the socket specification parameters, and during the conversion process, the microcontroller monitors the frequency and phase of the output voltage in real time to ensure that the distortion of the converted voltage waveform is less than a preset distortion, and adjusts the on-off frequency of the switch tube of the bridge circuit to realize voltage level matching and bidirectional power transmission between different sockets.

[0066] When the socket is connected to different mains voltage (such as 110V / 220V), the bridge circuit converts the input mains voltage to the target voltage according to the socket specification (such as target voltage 110V or 220V). During the conversion process, the MCU monitors the output voltage frequency (such as 50Hz / 60Hz) and phase in real time, ensuring that the waveform distortion is less than 5%, and by adjusting the switching tube on-off frequency, it realizes the voltage level matching between multiple sockets and bidirectional power transmission (such as 220V input for 110V device power supply, while directly supplying other 220V devices).

[0067] The bridge circuit structure adopts full-bridge inverter circuit (4 IGBT switching tubes) + LC filter. The input mains voltage is converted to DC by the bridge rectifier (such as KBPC3510), and then the target AC voltage is generated by the inverter module. The MCU locks the input voltage frequency and phase through the digital phase-locked loop (PLL) algorithm, ensures the output voltage frequency accuracy (such as 50Hz±0.1Hz), and controls the harmonic distortion (THD) within 5% through SPWM technology.

[0068] Bidirectional conversion control: when the input is 220V mains voltage and the device needs 110V, the bridge circuit works in buck inverter mode; when the input is 110V and the device needs 220V, start the boost inverter mode (achieved by adjusting the SPWM duty cycle); when multiple sockets are independently controlled, the MCU assigns independent switching frequency to each socket's bridge sub-module (such as socket 1 working at 60Hz, socket 2 working at 50Hz), avoiding mutual interference.

[0069] No external transformer is needed, directly adapting to 100-240V wide input, meeting the needs of cross-country travel and mixed use of devices in multiple regions; low distortion waveform (THD<5%) protects precision devices (such as notebook computer power adapter), avoiding device failure caused by waveform distortion of traditional converters; can supply power to 110V / 60Hz and 220V / 50Hz devices at the same time, for example, supplying power to American electric shavers and Chinese table lamps on the same power strip without mode switching.

[0070] In some embodiments, the microcontroller unit controls the output voltage and current of the corresponding socket to realize adaptive load adjustment for each socket according to the device power demand monitored by the load sensing sensor, including: when the load sensing sensor detects that the device power connected to the socket is less than the preset threshold, the microcontroller unit adjusts the output voltage to the lowest effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the lowest effective voltage, so that the device can work normally while reducing energy loss caused by internal resistance of the circuit.

[0071] When the load-aware sensor detects that the device power < preset threshold (such as 10W), the MCU adjusts the output voltage to the minimum effective voltage actually required by the device (such as from 9V to 5V when the mobile phone is on standby), and proportionally reduces the current in proportion to the voltage adjustment ratio (such as from 2A to 1.1A), to minimize the loss caused by the internal resistance of the circuit (such as the connecting line, the solder joint resistance) (P = I 2 R).

[0072] Low power detection and threshold setting The preset threshold can be set by factory configuration (such as 10W) or user customization, and the MCU calculates the power P = U x I in real time. When P < threshold for 5 seconds continuously, the energy-saving mode is triggered; the minimum effective voltage is matched through the device feature database (such as the minimum working voltage of the mobile phone charging chip is 4.5V, and the minimum 5V of the notebook computer USB interface), to ensure that the device does not restart and does not report errors.

[0073] Voltage-current coordinated regulation By adopting the "equal power factor" regulation strategy: output power P' = U' x I', where U' ≥ the minimum working voltage of the device, I' = P' / U', and I' ≤ the maximum allowable current of the device; for example, the current power of the device is 5W, and the minimum effective voltage is 5V, then I' = 1A (5W / 5V). Compared with the original fixed output, if it is 9V, the actual current may be 0.55A (5W / 9V), and the loss is (0.55A) 2 R; after adjustment, 5V / 1A, the loss is (1A) 2 R, when the actual demand power of the device is fixed, reducing the voltage needs to increase the current, but the circuit internal resistance loss is proportional to the square of the current, so when the device power is low, the actual voltage required by the device may be lower than the rated voltage (such as when the mobile phone is on standby, it does not need fast charging high voltage), at this time, the voltage is actively reduced to the minimum value that the device can still work, and the actual current of the device may not change or decrease (because power = voltage x current, if the power decreases, the voltage and current can be reduced at the same time). Correct adjustment should be: when the device power decreases, if the voltage is allowed to decrease (such as from fast charging 9V to 5V slow charging), the current may remain or decrease slightly, and the total loss (including converter itself loss and line loss) is reduced.

[0074] In the low power scenario (such as device standby, trickle charging), by reducing the voltage to the minimum effective value, the internal switch loss and line resistance loss of the converter are reduced, and the light load efficiency can be improved according to the measurement; for devices that rely on battery power (such as smart watch charger), provide just enough voltage and current to meet the demand, avoid "excessive power supply" caused by battery heating and life loss; general energy-saving strategy: without the cooperation of the device, actively adapt through sensor data, suitable for all types of low-voltage DC devices.

[0075] In some embodiments, the micro control unit is further configured to automatically identify the device type according to the device startup current waveform and the continuous power data collected by the load sensing sensor, and match the optimal voltage regulation strategy according to a preset device type database, wherein the preset device type database comprises voltage-power matching parameters of a plurality of power consuming devices.

[0076] The MCU collects the startup current waveform (such as the inrush current curve at the moment of starting) and the continuous power data (such as the power value when working stably) of the device when it is connected, matches it with the preset device type database (which stores the voltage-power matching parameters of devices such as mobile phones, laptops, and routers, such as mobile phone startup current ≤2A, laptop startup current 3-5A), automatically identifies the device type and calls the optimal regulation strategy (such as mobile phone priority fast charging strategy, laptop priority stable voltage strategy).

[0077] Feature data collection includes: startup phase: within 0.1-1 seconds after the device is inserted, collect current waveform at 10kHz sampling rate, capture inrush current peak value and duration (such as mobile phone fast charging device startup current rises to 2A, stabilizes after 0.2 seconds); continuous phase: after stable work, collect power data every 1 second, record average value and fluctuation range (such as router power stabilizes at 5W±0.5W).

[0078] Pattern matching algorithm: the database stores the feature vector of each device, such as mobile phone: [startup current peak value 1.8-2.4A, stable power 5-18W, voltage requirement 5 / 9 / 12V]; laptop: [startup current 3-6A, stable power 30-100W, voltage requirement 12-20V]; dynamic time warping (DTW) algorithm is used to match real-time waveform with database template, and when the matching degree is >80%, the device type is confirmed, and the corresponding strategy is called (such as laptop triggers "constant voltage mode", mobile phone triggers "fast charging protocol handshake").

[0079] No need for users to manually select device type, the system automatically identifies and optimizes the output, for example, to distinguish between mobile phones and power banks (the latter may need to be powered in reverse), to avoid incorrect regulation; provide exclusive strategies for the characteristics of different devices (such as the startup surge of motor class devices, the voltage sensitivity of precision chips), to reduce compatibility problems caused by "one-size-fits-all" regulation; through general sensors and database matching, support for adding new device types only requires updating the database, without the need for hardware changes.

[0080] For example, the micro control unit stores the power regulation data of the historical connected devices, dynamically optimizes the response speed and accuracy of voltage regulation by analyzing the voltage adaptation process when the device is connected repeatedly, so that the voltage adjustment time when the same type of device is connected again is shortened.

[0081] The MCU stores the power adjustment data of the historical connection devices (e.g., when device A is first connected, the voltage is reduced from 20V to 15V in 0.5 seconds, and the adjustment step is 2V), and when the same type of device is connected again, the voltage adaptation process in the historical data (e.g., the optimal step-down step, the stabilization time) is analyzed to dynamically optimize the response speed and accuracy of the adjustment algorithm, so that the voltage adjustment time of the same type of device is shortened by more than 50% (e.g., from 0.5 seconds to 0.25 seconds).

[0082] Data storage and management store the content including: the first connection time of the device, the type (identified by embodiment 4), the voltage / current change curve in the adjustment process, the stabilization time, and the final parameters (U_target, I_target) by establishing a mapping table of device ID and adjustment log. Hash table is used to quickly retrieve historical data of the same type of device, for example, by generating a unique key value (e.g., "mobile phone-9V" corresponds to a set of optimized parameters) through device type + rated voltage.

[0083] Optimization algorithm implementation: when adjusting for the first time, a conservative strategy (small step-down step, step 1V) is adopted, and the stabilization time is recorded; when connecting repeatedly, the step is adjusted according to the historical data (e.g., it is known that a certain type of mobile phone can accept a step-down step of 3V / second without triggering protection, so it is directly adjusted with a large step), and the target voltage is predicted (e.g., skipping the intermediate redundant steps, directly reducing from 310V DC after rectification to the target 9V DC, without passing through 20V, 15V, etc. Intermediate values).

[0084] When the same type of device is connected again, the voltage adjustment time is shortened from "seconds" to "hundred milliseconds", reducing the waiting time of the device (e.g., when a notebook computer is charging, it does not need to re-negotiate the voltage and directly enters the optimal state); the longer the system is used, the more accurate the adjustment strategy, especially suitable for multiple device scenarios in a family (e.g., the same mobile phone is charged multiple times, and the adaptation speed gradually improves); by predicting the target parameters, energy loss in multiple invalid adjustment processes is avoided, and dynamic adjustment efficiency is improved.

[0085] For example, by introducing a deep learning neural network, the system does not need to rely on a pre-set device type database, but generates a device feature model by training in real time through the device startup current waveform, steady-state power curve, and voltage response data. When a new device is first connected, the system extracts the waveform features through a convolutional neural network (CNN) and compares them with the historical learning feature vectors to dynamically expand the device type library, achieving adaptive identification and adjustment strategy generation for unknown devices.

[0086] Data collection and feature engineering: The current waveform (including the startup surge phase) of the device during the first 2 seconds of access is collected by the sensor at a sampling rate of 20 kHz and converted into a grayscale image (horizontal axis time, vertical axis current amplitude) as the input of the CNN; time domain features (such as surge peak, rise time) and frequency domain features (harmonic distribution after FFT) are extracted to construct a multi-dimensional feature vector.

[0087] Incremental learning neural network uses a ResNet-18 lightweight model, and the initial weights are obtained by pre-training common devices (mobile phones, laptops, routers); when a new device is connected, if the matching degree is less than 70%, incremental learning is triggered: new feature data is added to the training set, the model is updated using transfer learning, and "catastrophic forgetting" is avoided through dynamic weight distribution; generate device-specific adjustment strategy: according to the identified device category (such as "unknown charging device"), generate an initial voltage adjustment sequence (such as reducing the voltage by 1V steps, and waiting for 200ms to detect the device response at each step) through reinforcement learning algorithm (Q-Learning).

[0088] No need for manual maintenance of the database, automatically identify new devices appearing on the market (such as new smartwatches, customized industrial modules), solve the update lag problem of traditional preset databases; as the number of connected devices increases, the recognition accuracy gradually improves, and the system becomes more "intelligent"; identify potential device faults (such as battery aging) in advance through waveform abnormal patterns (such as startup current oscillation).

[0089] In some embodiments, the load-aware sensor includes a current transformer and a voltage sensor integrated on the power supply circuit of each outlet, which respectively collect the input current and port voltage of the device in real time, and the microcontroller unit calculates the real-time power based on the collected data and performs anomaly detection, and when a power mutation exceeding the preset mutation range of the rated value is detected, the overvoltage protection or overcurrent protection mechanism is triggered to cut off the power supply of the corresponding outlet.

[0090] The load-aware sensor is composed of a current transformer (CT, such as TA123) and a voltage sensor (such as a voltage dividing resistor network), integrated on the power supply circuit of each outlet, which collects the input current and port voltage of the device in real time. The MCU calculates the real-time power and detects anomalies: when the power mutation exceeds the preset range of the rated value (such as ±30%), the overvoltage / overcurrent protection is triggered, and the power supply of the corresponding outlet is immediately cut off (response time <100μs).

[0091] Sensor hardware design: Current sensor uses a miniature closed-loop Hall sensor with an accuracy of ±1% and supports a 0-5A measurement range. It is connected in series in the power supply circuit. The voltage sensor reduces the port voltage (up to 220V AC) to the 0-3.3V range that the MCU ADC can receive through resistance division (such as a 100kΩ+10kΩ voltage division circuit). The sampling frequency is 1kHz.

[0092] Abnormality detection logic: Real-time power P = U x I, with a preset normal fluctuation range (such as ±10% of the rated power). When P is detected to change by more than ±30% within 200μs (such as a sudden increase in current due to device short circuit or a sudden drop in voltage due to loose connection), a hardware interrupt is triggered immediately, and the MCU cuts off the relay or MOSFET switch for the corresponding socket through the GPIO. The protection threshold can be dynamically adjusted according to the device type (such as ±20% fluctuation for motor class devices and only ±5% for precision devices).

[0093] Compared with traditional hardware fuses (response time >10ms), the electronic protection mechanism can cut off the power supply within 100μs, effectively preventing devices from being damaged by transient overvoltage / overcurrent (such as lightning surge, internal device short circuit). Each socket is independently monitored, and a single socket failure does not affect other sockets. The fault type (such as overvoltage / overcurrent event time, waveform) is recorded through historical data, facilitating post-troubleshooting. For old devices that do not support protocol communication (such as non-smart home appliances), the real-time sensor data provides an equivalent "smart protection" safety mechanism, expanding the protection range.

[0094] For example, the overvoltage and overcurrent protection mechanism of the embodiment introduces a fuzzy logic system to finely classify abnormal events (such as distinguishing between "lightning surge", "device short circuit", and "poor contact") and execute different self-healing strategies based on the classification results. For example, when detecting "poor contact" type abnormalities, it automatically tries to reconnect 3 times to avoid false disconnection. When detecting "device short circuit", it immediately cuts off the power and locks the socket.

[0095] Fuzzy rule construction: Input variables: power mutation amplitude (large / medium / small), mutation duration (instantaneous / short-term / long-term), voltage and current phase difference (normal / abnormal); Output variables: abnormal type (7 categories: surge, short circuit, poor contact, overload, reverse current, voltage oscillation, unknown), self-healing action (retry / power off / alarm); 27 fuzzy rules are defined (such as "large power mutation + instantaneous duration + normal phase difference" → "lightning surge", triggering energy storage capacitor discharge protection).

[0096] Self-healing strategy execution: contact failure handling: detect power intermittent sag (more than 3 times per 10 seconds), control the socket relay to open-close cycle (interval 500 ms), try to restore the connection; surge protection enhancement: after identifying as lightning surge, in addition to cutting off the power supply, trigger the input side MOV pressure sensitive resistance bypass at the same time, clamp the residual voltage to a safe value; data feedback: abnormal event classification results are stored in the local log and sent to the user's mobile phone APP through Bluetooth, providing fault diagnosis suggestions.

[0097] For example, the abnormal event risk assessment and response threshold dynamic adjustment formula designed for overvoltage protection includes:

[0098] ;

[0099] Where: R is the comprehensive risk index of abnormal events (dimensionless, value range [0, 1], the closer R is to 1, the higher the risk, and the higher the priority of triggering protection action); γ is the device type sensitivity coefficient (dimensionless, value range [0.8, 1.5], automatically configured by the rated parameters of the device: precision chip class devices γ=1.5, ordinary household appliances γ=1.0); ωv is the voltage deviation weight (dimensionless, value range [0, 1], default 0.6, automatically increased to 0.8 when the device contains MCU); ωi is the current deviation weight (dimensionless, value range [0, 1], ωv+ωi=1, automatically increased to 0.7 for motor class devices); V is the real-time voltage (normalized value [Vmin, Vmax], converted to dimensionless value by Z-score); Vnom is the rated voltage of the device (also normalized); I is the real-time current (normalized value [Imin, Imax]); Inom is the rated current of the device (normalized); τ is the abnormal duration (seconds, calculated by sliding window, exceeding 5 seconds triggers exponential risk growth); τ0 is the reference time constant (fixed value 1 second); sgn(ΔP) is the power change sign function (ΔP>0 takes 1 for power surge, -1 for sudden drop, and 0 for stable); t is the time since the last protection action (seconds, used to attenuate historical risk influence and avoid repeated triggering); tdecay is the decay time constant (adaptive value, 30 seconds for precision devices, 60 seconds for ordinary devices).

[0100] The formula fuses voltage deviation, current deviation, abnormal duration, power change direction and historical protection interval five dimensions, and realizes the differentiation of protection strategy through dynamic weight (ωv / ωi) and device type sensitive coefficient (γ). For example, for voltage-sensitive MCU devices (such as single-chip development boards), the voltage deviation weight is increased to 0.8, and γ=1.5 amplifies the risk perception, ensuring that micro-voltage fluctuations can also trigger early warning. In some embodiments, a separate power management module is arranged inside the power converter body, which includes a filter circuit and an energy storage capacitor. The filter circuit is used to filter the high-frequency noise generated during the operation of the step-down circuit and the bridge circuit, and the energy storage capacitor maintains stable power supply when the input voltage fluctuates instantaneously, to ensure the continuous monitoring function of the micro-control unit and the load perception sensor.

[0101] By setting the abnormal duration amplification term (1+τ / τ0*sgn(ΔP)): when the power suddenly increases (such as motor starting) and the duration exceeds 1 second, the risk index increases linearly (100% increase in risk for every additional 1 second), avoiding false triggering by short-term interference; the historical decay factor (e -t / tdecay ): the closer to the last protection time (such as t=0), the more cautious the current risk assessment (exponential decay to avoid frequent actions), and the decay is faster for precision devices (tdecay=30 seconds) to reduce downtime losses.

[0102] Voltage / current parameters are normalized by device safety interval [Vmin, Vmax] (for example, for a rated 5V device, the safety interval is 4.5V-5.5V, and V=5.2V corresponds to a normalized value of 0.4); time-related parameters are dimensionless with reference constants (τ0 / tdecay), ensuring consistency in cross-device type calculations.

[0103] Power change direction perception distinguishes between "dangerous surge" (such as short circuit leading to sudden current increase, ΔP>0 amplifying risk) and "safe drop" (such as device normal shutdown, ΔP<0 suppressing risk), solving the defect that traditional overcurrent protection cannot identify power change trend.

[0104] Compared with traditional fixed threshold protection (such as cutting off power immediately when current exceeds 1.2 times of rated value), the formula supports dynamic adjustment of risk level:

[0105] When R∈[0.3,0.6], trigger early warning but not cut off, only record log (suitable for refrigerators and other devices that allow temporary fluctuations); when R≥0.7, cut off according to device priority (game theory model of embodiment 11) (non-critical devices are cut off first), and the trigger threshold of precision devices is reduced to 0.5, with a 30% increase in protection response speed.

[0106] For electromagnetic compatibility scenarios (such as voltage glitches caused by nearby motor start-stop), the false trigger rate is reduced from 20% of traditional threshold detection to less than 5% through τ duration time judgment and tdecay historical decay, especially suitable for complex power grid environment in industrial control scenarios.

[0107] Without manual configuration of protection parameters, the system automatically generates coefficients such as γ, ωv, and tdecay based on calibration data (Vnom, Inom, Vmax, Imax) when the device is first connected, covering all device types from mobile phone chargers (low sensitivity) to medical devices (high sensitivity).

[0108] The power converter body is built-in with an independent power management module, including a filter circuit (LC filter) and an energy storage capacitor (such as 1000 μF electrolytic capacitor). The filter circuit filters out high-frequency noise (such as harmonics above 100 kHz) generated by the buck / bridge circuit, avoiding interference with the MCU and sensor; the energy storage capacitor maintains stable power supply for more than 50 ms when the input voltage fluctuates momentarily (such as immediately after power failure), ensuring uninterrupted monitoring function.

[0109] Filter circuit design: two-stage LC filtering: the first stage inductance (100 μH) + capacitance (100 nF) filters out differential mode noise, and the second stage common mode inductance (2 mH) + Y capacitance (470 pF) filters out common mode noise, ensuring that the peak-to-peak power supply noise to the MCU is less than 50 mV; the filter circuit is located after the mains input and before each functional module, forming an independent power supply channel.

[0110] The energy storage capacitor capacity is calculated based on the standby power consumption of the system (such as total power consumption of MCU + sensor 50 mW, which needs to maintain 50 ms power supply, then capacitor capacity C = (P x t) / (0.5 x ΔV 2 ) ≈ 1000 μF @ 5V); in combination with the diode rectifier bridge, when the input voltage is interrupted, the energy storage capacitor supplies power to the control circuit through the discharge circuit, ensuring that the MCU completes the current data processing and records abnormal events (such as temporary power failure).

[0111] After filtering out high-frequency noise, the sampling accuracy of the MCU is improved from ±2% to ±0.5%, avoiding false triggering of the protection mechanism due to noise; when the input voltage fluctuates (such as voltage sag caused by air conditioner startup), the energy storage capacitor maintains the operation of the monitoring system, preventing false power cut-off, while ensuring that the protection mechanism is triggered based on stable data, reducing false actions; the independent power management module isolates the main power circuit from the control circuit, avoiding direct impact of main circuit failure (such as bridge circuit short circuit) on the control unit, improving overall robustness.

[0112] In some embodiments, the power converter body surface is provided with a human-computer interaction interface, which includes a state indicating lamp and a parameter adjustment button, and the voltage upper limit and current protection threshold of any one socket are set through the adjustment button.

[0113] The power converter body surface is provided with a human-computer interaction interface, which includes a state indicating lamp (such as a red / green indicating lamp corresponding to each socket, showing normal / abnormal voltage) and a parameter adjustment button (such as "+" "-" key), and the user can set the voltage upper limit (such as limiting the highest output of 12V of a certain USB port) and the current protection threshold (such as setting 2A overcurrent protection) for any one socket through the button, and the set parameters are stored in the MCU non-volatile memory (EEPROM).

[0114] Hardware interface design: the state indicating lamp uses RGB LED, and each socket corresponds to an indicating lamp: green = normal, red = overvoltage / overcurrent, yellow = standby; the adjustment button uses a waterproof micro switch, and a LCD small screen (optional) is used to display the current socket number, voltage, current, threshold and other parameters, and the socket can be switched through the button (such as long press to switch to socket 1, and short press to adjust the threshold).

[0115] Software interaction logic: the user long presses the "set" key to enter the configuration mode, selects the socket (1-4) through the "up / down" key, and then adjusts the voltage upper limit (step 1V) and current threshold (step 0.1A) through the "left / right" key.

[0116] Safety mechanism: the voltage upper limit shall not exceed 120% of the rated voltage of the device, and the current threshold shall not exceed the maximum carrying capacity of the socket (such as USB-C port default maximum 3A, and the user cannot set more than 3.5A).

[0117] It meets the needs of professional users or special devices (such as laboratory equipment needs to fix 15V voltage, which can be manually set to prevent automatic adjustment from being excessive), and improves flexibility; the working state of each socket can be mastered in real time through the indicating lamp, without relying on mobile phone APP, which is suitable for no network environment or rapid troubleshooting; the user can set a more stringent protection threshold (such as current fluctuation exceeding 5% triggering protection) for high-value equipment (such as single-lens reflex camera charger), which is more delicate than the default setting.

[0118] In some embodiments, by analyzing the user's historical settings of the socket parameters (such as the user often sets the voltage upper limit of socket 1 to 12V to charge the tablet computer) and the device access frequency, the "user-device-parameter" mapping relationship is generated by using the association rule algorithm (such as Apriori algorithm), and when the same device or the same use scene is detected, the user's preferred adjustment strategy is automatically called to realize "unconscious" personalized adaptation.

[0119] User habit modeling includes: collecting data: voltage upper limit, current threshold, device access time (e.g. user accesses mobile phone charging at 8pm every day), device connection duration set by user through human-machine interface (embodiment 8); association rule mining: identifying high-frequency patterns (e.g. "device type = mobile phone + time = 20:00-22:00" → "voltage = 9V + current threshold = 2.4A"), setting rules with confidence ≥80% into user profile.

[0120] Active adaptation mechanism includes: time trigger: reaching a preset time period (e.g. 8pm), even if the device is not accessed, the socket parameters are adjusted to the user's common configuration in advance, reducing the waiting time after the device is accessed; device recognition trigger: when the deep learning model of embodiment 9 identifies that "user's common mobile phone" is accessed, the regular detection process is skipped, and the historical optimal parameters are directly applied (voltage adjustment time is shortened from 1 second to 200ms); user can temporarily modify parameters, system automatically judges whether it is long-term preference (e.g. if a parameter setting lasts for more than 3 times, the rule is updated).

[0121] In some embodiments, by predicting the power demand curve of the device in the next 5-10 minutes through the use of long short-term memory network (LSTM), combining model predictive control (MPC) algorithm to adjust the output parameters of the step-down circuit and bridge circuit in advance, the internal loss and line loss of the converter are minimized under the premise of meeting the power demand of the device. For example, when it is predicted that the mobile phone will soon enter the fast charging stage (power from 5W to 18W), the output voltage is raised to 9V in advance to avoid voltage overshoot caused by temporary adjustment.

[0122] Time series data modeling collects historical power data (timestamp, real-time power, device status label), builds a sliding window (window size 300 samples, about 5 minutes) input LSTM network, predicts power values at 10 future time points (2 minutes), prediction accuracy ≥90%; if the device temperature rises (through the built-in temperature sensor), the prediction model is corrected to reduce the power upper limit to avoid overheating.

[0123] Model predictive control (MPC) establishes a converter loss model: total loss = switch loss (related to frequency) + conduction loss (I²R) + iron loss (related to voltage fluctuation); optimization objective function: minimize (total loss in the next 10 minutes), constraint condition: output voltage fluctuation ≤±3%, current ≤ device rated value; control parameters (PWM duty cycle, bridge circuit switching frequency) are optimized once every 200ms, realizing advance adjustment.

[0124] In some embodiments, when multiple devices are simultaneously accessed, a multi-agent game model is constructed, each socket as an agent, by dynamically adjusting the output voltage and current strategy, minimizing the overall system loss and avoiding input side overload on the premise of meeting the power demand of its own device. The algorithm is based on the Nash equilibrium theory, so that the adjustment strategy of each socket reaches a "win-win" state, for example, when high-power devices (notebooks) and low-power devices (Bluetooth earphones) share input resources, the optimal voltage level is automatically allocated.

[0125] Game model construction: define the agent strategy space: the voltage range [U_min, U_max] and current range [I_min, I_max] that each socket can adjust; Design of profit function: single socket profit = (device demand power / actual output power) - (self loss + interference coefficient to other sockets), the interference coefficient is positively correlated with the voltage difference of adjacent sockets; Use distributed gradient descent algorithm, each socket exchanges the current strategy parameters through CAN bus, updates the strategy every 50ms, until Nash equilibrium is reached.

[0126] Hardware co-design by equipping each socket with an independent communication module (such as SPI interface), the main MCU as a coordinator collects the status of each socket; The total current sensor is set at the input side, when the total current approaches the rated value (such as 10A), the load balancing mechanism is triggered, and the power supply of high-priority devices (such as medical devices) is preferentially guaranteed.

[0127] Please refer to Figure 3 , Figure 3 is a schematic flowchart of a control method of an intelligent power converter system based on adaptive load regulation provided by an embodiment of the present application. The execution device of the method is the micro control unit of the intelligent power converter system based on adaptive load regulation provided by any embodiment of the present application.

[0128] As Figure 3 shown, the provided method includes steps S101 to S103.

[0129] Step S101. When the device connected to the socket needs low-voltage direct-current power supply, control the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current.

[0130] Step S102. When the socket is connected to different input voltages, control the bridge circuit to convert the input AC voltage to the target voltage suitable for the socket.

[0131] Step S103. According to the device power demand monitored by the load sensing sensor, control the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket to realize adaptive load regulation for each socket.

[0132] In some embodiments, when the device connected to the socket requires low-voltage direct current power supply, the micro control unit controls the voltage reduction circuit to reduce the input voltage to the required voltage of the device and adjust the output current, including: when the device is inserted into the socket, the load sensing sensor obtains the rated voltage parameter of the device in real time, and the micro control unit controls the voltage reduction circuit to step down from the input alternating current voltage to the required direct current voltage of the device according to the rated voltage parameter, and dynamically adjusts the current according to the corresponding real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

[0133] In some embodiments, when the socket connects different input mains voltage, the micro control unit controls the bridge circuit to convert the input mains voltage to the target voltage suitable for the socket, including: when the socket is connected to the mains as input, the bridge circuit converts the mains power corresponding to the mains according to the socket specification parameters to the target voltage suitable for the socket, and monitors the frequency and phase of the output voltage in real time through the micro control unit during the conversion process, ensures that the distortion degree of the converted voltage waveform is less than the preset distortion degree, and realizes the voltage level matching and bidirectional power transmission between different sockets through the switching tube on-off frequency adjustment of the bridge circuit.

[0134] In some embodiments, according to the device power demand monitored by the load sensing sensor, the micro control unit controls the voltage reduction circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket to realize adaptive load adjustment for each socket, including: when the load sensing sensor detects that the power of the device connected to the socket is less than the preset threshold, the micro control unit adjusts the output voltage to the lowest effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the lowest effective voltage, so that the device can meet the normal working condition while reducing the energy loss caused by the internal resistance of the circuit.

[0135] In some embodiments, the micro control unit is also used to automatically identify the device type according to the device start current waveform and continuous power data collected by the load sensing sensor, and match the optimal voltage adjustment strategy according to the preset device type database, wherein the preset device type database includes voltage-power matching parameters of various electric devices.

[0136] For example, the micro control unit stores the power adjustment data of the historical connected devices, dynamically optimizes the response speed and accuracy of voltage adjustment by analyzing the voltage adaptation process when the device is repeatedly connected, so that the voltage adjustment time is shortened when the same type of device is connected again.

[0137] In some embodiments, the load-aware sensor includes a current transformer and a voltage sensor integrated on the power supply circuit of each socket, which respectively collect the input current and port voltage of the device in real time, and the micro control unit calculates the real-time power according to the collected data and performs abnormality detection, and when detecting that the power mutation exceeds the preset mutation range of the rated value, triggers the over-voltage protection or over-current protection mechanism to cut off the power supply of the corresponding socket.

[0138] In some embodiments, the power converter body is internally provided with a separate power management module, which includes a filter circuit and an energy storage capacitor, the filter circuit is used to filter out high-frequency noise generated during the operation of the step-down circuit and the bridge circuit, and the energy storage capacitor maintains stable power supply when the input voltage fluctuates temporarily, to ensure the continuous monitoring function of the micro control unit and the load-aware sensor.

[0139] In some embodiments, the surface of the power converter body is provided with a human-computer interaction interface, which includes a state indicating lamp and a parameter adjustment button, and the voltage upper limit and current protection threshold of any socket are set through the adjustment button.

[0140] It should be noted that, for the convenience and brevity of description, the specific working process of the control method of the adaptive load regulation based intelligent power converter system and each step described above can be clearly understood by those skilled in the art, and the corresponding process in the adaptive load regulation based intelligent power converter system embodiments described above can be referred to, which will not be described here.

[0141] Please refer to Figure 4 , Figure 4 is a structural schematic block diagram of the micro control unit provided by the embodiment of the application. The micro control unit includes a processor, a memory and a network interface connected through a device bus, wherein the memory can include a storage medium and an internal memory.

[0142] The storage medium can store an operating device and a computer program. The computer program includes program instructions, which, when executed, can cause the processor to execute any one embodiment of the control method of the adaptive load regulation based intelligent power converter system.

[0143] The processor is used to provide computing and control capabilities to support the operation of the entire micro control unit.

[0144] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium, which, when executed by the processor, can cause the processor to execute any one embodiment of the adaptive load regulation based intelligent power converter system method.

[0145] The network interface is used for network communication, such as sending assigned tasks, etc. Figure 4 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the terminal to which the scheme of the present application is applied. The specific micro control unit can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0146] It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0147] In one embodiment, the processor is configured to run a computer program stored in the memory to perform the following steps:

[0148] When the device connected to the socket needs low-voltage direct-current power supply, the control reduces the input voltage to the voltage required by the device and adjusts the output current;

[0149] When the socket is connected to different mains voltage inputs, the control converts the input mains voltage to the target voltage suitable for the socket;

[0150] According to the power requirement of the device monitored by the load sensing sensor, the control automatically adjusts the output voltage and current of the corresponding socket to realize adaptive load regulation of each socket.

[0151] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the processor described above can refer to the corresponding process in the method embodiments described in the above embodiments, which will not be described here.

[0152] The computer readable storage medium of the embodiments of the present application stores a computer program, the computer program includes program instructions, and the processor executes the program instructions to realize the steps of the control method of the intelligent power converter system based on adaptive load regulation provided by the above embodiments of the present application.

[0153] The computer readable storage medium can be an internal storage unit of the micro control unit, such as a hard disk or a memory of the micro control unit. The computer readable storage medium can also be an external storage device of the micro control unit, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc.

[0154] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An intelligent power converter system based on adaptive load regulation, characterized by, The utility model relates to a power converter, comprising: a power converter body provided with a plurality of different types of sockets, the power converter body is built in load sensing sensor, micro control unit, voltage reduction circuit and bridge circuit, the load sensing sensor is electrically connected with the micro control unit, is used for monitoring the power requirement of the equipment connected to each socket in real time and transmitting the corresponding monitoring signal to the micro control unit, the micro control unit is electrically connected with the voltage reduction circuit and bridge circuit respectively, is used for controlling the voltage reduction circuit and bridge circuit to adjust output voltage and current according to the monitoring signal transmitted by the load sensing sensor, when the equipment connected to the socket needs low-voltage direct-current power supply, the micro control unit controls the voltage reduction circuit to reduce the input voltage to the voltage required by the equipment and adjusts the output current, when the socket is connected to different input voltages, the micro control unit controls the bridge circuit to convert the input AC voltage into a target voltage suitable for the socket, including: when the socket is connected to the AC power supply as input, the bridge circuit converts the AC power supply corresponding to the socket into a target voltage suitable for the socket according to the socket specification parameters, and monitors the frequency and phase of the output voltage in real time through the micro control unit during the conversion process to ensure that the distortion degree of the converted voltage waveform is less than the preset distortion degree, and the voltage level matching and bidirectional power transmission between different sockets are realized through the on-off frequency adjustment of the bridge circuit's switching tube, the micro control unit controls the voltage reduction circuit and bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the power requirement of the equipment monitored by the load sensing sensor, to realize adaptive load regulation for each socket, the load sensing sensor includes a current transformer and a voltage sensor, the current transformer and the voltage sensor are integrated on the power supply circuit of each socket to real-time collect the input current and port voltage of the equipment, the micro control unit calculates the real-time power according to the collected data and performs abnormality detection, when the power mutation exceeds the preset mutation range of the rated value, the overvoltage protection or overcurrent protection mechanism is triggered to cut off the power supply of the corresponding socket, wherein the abnormal event risk assessment and response threshold adjustment formula designed for overvoltage protection includes: ； wherein: R is the comprehensive risk index of abnormal events, the value range is [0, 1], R is closer to 1, indicating higher risk, and the priority of triggering protection action is higher, γ is the device type sensitivity coefficient, the value range is [0.8, 1.5], which is automatically configured by the rated parameters of the device, γ=1.5 for precision chip devices, and γ=1.0 for ordinary household appliances, ωv is the voltage deviation weight, the value range is [0, 1], ωi is the current deviation weight, the value range is [0, 1], and ωv+ωi=1, V is the real-time voltage, Vnom is the rated voltage of the device, I is the real-time current, Inom is the rated current of the device, τ is the abnormal duration, τ0 is the reference time constant, the fixed value is 1 second, sgn(ΔP) is the power change sign function, t is the time from the last protection action, and tdecay is the decay time constant.

2. The system of claim 1, wherein, When the device connected to the socket needs low-voltage direct-current power supply, the micro control unit controls the voltage reduction circuit to reduce the input voltage to the voltage required by the device and adjust the output current, including: When the device is inserted into the socket, the load sensing sensor obtains the rated voltage parameter of the device in real time, and the micro control unit controls the voltage reduction circuit to step down from the input alternating voltage to the direct-current voltage required by the device according to the rated voltage parameter, and dynamically adjusts the current according to the real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

3. The system of claim 1, wherein, According to the power demand of the device monitored by the load sensing sensor, the micro control unit controls the voltage reduction circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket to realize adaptive load adjustment of each socket, including: When the load sensing sensor detects that the power of the device connected to the socket is less than the preset threshold, the micro control unit adjusts the output voltage to the lowest effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the lowest effective voltage, so that the device can meet the normal working condition while reducing the energy loss caused by the internal resistance of the circuit.

4. The system of claim 1, wherein, The micro control unit is also used to automatically identify the type of the device according to the device start current waveform and continuous power data collected by the load sensing sensor, and to match the optimal voltage adjustment strategy according to the preset device type database, wherein the preset device type database includes voltage-power matching parameters of various electrical devices.

5. The system of claim 4, wherein, The micro control unit stores the power adjustment data of the historical connected devices, dynamically optimizes the response speed and accuracy of the voltage adjustment by analyzing the voltage adaptation process when the device is repeatedly accessed, so that the voltage adjustment time of the same type of device when accessed again is shortened.

6. The system of claim 1, wherein, The power converter body is internally provided with a separate power management module, the power management module includes a filter circuit and an energy storage capacitor, the filter circuit is used to filter out high-frequency noise generated during the operation of the voltage reduction circuit and the bridge circuit, and the energy storage capacitor maintains stable power supply when the input voltage fluctuates instantaneously, so as to ensure the continuous monitoring function of the micro control unit and the load sensing sensor.

7. The system of claim 1, wherein, The surface of the power converter body is provided with a man-machine interaction interface, the man-machine interaction interface includes a state indicating lamp and a parameter adjustment button, and the voltage upper limit and current protection threshold of any socket are set through the adjustment button.

8. A control method of an intelligent power converter system based on adaptive load regulation, characterized by, The method is applied to the intelligent power converter system of any one of claims 1-7, and the method comprises: When the device connected to the socket needs low-voltage direct-current power supply, the micro control unit controls the voltage reduction circuit to reduce the input voltage to the voltage required by the device and adjust the output current; When the socket is connected to different input voltages, the bridge circuit is controlled to convert the input mains voltage into a target voltage suitable for the socket; According to the power demand of the device monitored by the load sensing sensor, the micro control unit controls the voltage reduction circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket to realize adaptive load adjustment of each socket.

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